Python Performance Optimization

关于

This skill provides a comprehensive toolkit for identifying and resolving performance issues in Python applications. It guides Claude through advanced profiling techniques—including CPU, memory, and line-by-line analysis—using industry-standard tools like cProfile and py-spy. By implementing best practices for data structures, algorithmic efficiency, and memory management (such as generators and __slots__), this skill ensures Python code is production-ready, scalable, and highly efficient.

主要功能

• Advanced memory optimization using __slots__ and efficient data structures
• CPU and memory profiling using cProfile, memory_profiler, and py-spy
• Computational acceleration using NumPy and caching strategies like lru_cache
• Implementation of high-performance patterns like list comprehensions and generators
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• Granular line-by-line performance analysis for precise bottleneck detection

使用场景

• Identifying and fixing memory leaks in long-running Python services
• Speeding up slow data processing pipelines and API response times
• Optimizing CPU-intensive algorithms for production-grade scalability